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Wei W, Shang Y, Peng Y, Cong R. Research Progress of Noise in High-Speed Cutting Machining. SENSORS (BASEL, SWITZERLAND) 2022; 22:3851. [PMID: 35632259 PMCID: PMC9146239 DOI: 10.3390/s22103851] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 05/09/2022] [Accepted: 05/16/2022] [Indexed: 06/15/2023]
Abstract
High-speed cutting technology has become a development trend in the material processing industry. However, high-intensity noise generated during high-speed cutting exerts a potential effect on the processing efficiency, processing accuracy, and product quality of the workpiece; it may even cause hidden safety hazards. To conduct an in-depth study of noise in high-speed cutting machining, this work reviews noise sources, noise collection and numerical recognition, noise control, and condition monitoring based on acoustic signals. First, this article introduces noise sources, noise signal acquisition equipment, and analysis software. It is pointed out that how to accurately classify and recognize the target signal in the complex high-speed machining environment is one of the focuses of scholars' research. Then, it points out that a computer achieves high accuracy and practicability in signal analysis, processing, and result display. Second, in the aspect of noise signal processing, the characteristics of noise signals are analyzed. It is pointed out that accurately analyzing the characteristics of different noise source signals and adopting appropriate methods for identification and processing are the necessary conditions for effectively controlling and reducing the noise in the process of high-speed cutting. The advantages and applicable fields of artificial intelligence algorithms in processing mixed noise source signals with different frequency characteristics are compared, providing ideas for studying the mechanism of noise generation and the identification of noise sources. Third, in terms of noise control, a detailed overview is provided from the aspects of the treatment of the noise source that contributes the most to the overall noise, the improvement of the tool structure, the optimization of cutting parameters, and the analysis of contact factors between the tool and the workpiece. It provides an effective way for noise control in the process of high-speed cutting. In addition, the application of acoustic signals to condition monitoring is also thoroughly analyzed. The practical application value of condition monitoring based on acoustic signals in high-speed machining is highlighted. Finally, this paper summarizes the positive significance of noise research in high-speed machining and identifies key problems and possible research methods that require further study in the future.
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Kuntoğlu M, Aslan A, Pimenov DY, Usca ÜA, Salur E, Gupta MK, Mikolajczyk T, Giasin K, Kapłonek W, Sharma S. A Review of Indirect Tool Condition Monitoring Systems and Decision-Making Methods in Turning: Critical Analysis and Trends. SENSORS (BASEL, SWITZERLAND) 2020; 21:E108. [PMID: 33375340 PMCID: PMC7794675 DOI: 10.3390/s21010108] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Revised: 12/20/2020] [Accepted: 12/22/2020] [Indexed: 01/29/2023]
Abstract
The complex structure of turning aggravates obtaining the desired results in terms of tool wear and surface roughness. The existence of high temperature and pressure make difficult to reach and observe the cutting area. In-direct tool condition, monitoring systems provide tracking the condition of cutting tool via several released or converted energy types, namely, heat, acoustic emission, vibration, cutting forces and motor current. Tool wear inevitably progresses during metal cutting and has a relationship with these energy types. Indirect tool condition monitoring systems use sensors situated around the cutting area to state the wear condition of the cutting tool without intervention to cutting zone. In this study, sensors mostly used in indirect tool condition monitoring systems and their correlations between tool wear are reviewed to summarize the literature survey in this field for the last two decades. The reviews about tool condition monitoring systems in turning are very limited, and relationship between measured variables such as tool wear and vibration require a detailed analysis. In this work, the main aim is to discuss the effect of sensorial data on tool wear by considering previous published papers. As a computer aided electronic and mechanical support system, tool condition monitoring paves the way for machining industry and the future and development of Industry 4.0.
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Affiliation(s)
- Mustafa Kuntoğlu
- Mechanical Engineering Department, Technology Faculty, Selcuk University, Selçuklu, 42130 Konya, Turkey;
| | - Abdullah Aslan
- Mechanical Engineering Department, Engineering and Architecture Faculty, Selcuk University, Akşehir, 42130 Konya, Turkey;
| | - Danil Yurievich Pimenov
- Department of Automated Mechanical Engineering, South Ural State University, Lenin Prosp. 76, 454080 Chelyabinsk, Russia;
| | - Üsame Ali Usca
- Mechanical Engineering Department, Engineering and Architecture Faculty, Bingöl University, 12000 Bingöl, Turkey;
| | - Emin Salur
- Department of Metallurgical and Materials Engineering, Selcuk University, Selçuklu, 42130 Konya, Turkey;
| | - Munish Kumar Gupta
- Department of Automated Mechanical Engineering, South Ural State University, Lenin Prosp. 76, 454080 Chelyabinsk, Russia;
- Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan 250100, China
| | - Tadeusz Mikolajczyk
- Department of Production Engineering, UTP University of Science and Technology, Al. Prof. S. Kaliskiego 7, 85-796 Bydgoszcz, Poland;
| | - Khaled Giasin
- School of Mechanical and Design Engineering, University of Portsmouth, Portsmouth PO1 3DJ, UK;
| | - Wojciech Kapłonek
- Department of Production Engineering, Faculty of Mechanical Engineering, Koszalin University of Technology, Racławicka 15-17, 75-620 Koszalin, Poland;
| | - Shubham Sharma
- Department of Mechanical Engineering, IKG Punjab Technical University, Jalandhar-Kapurthala Road, Kapurthala, Punjab 144603, India;
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Şahinoğlu A, Rafighi M. Investigation of Vibration, Sound Intensity, Machine Current and Surface Roughness Values of AISI 4140 During Machining on the Lathe. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2019. [DOI: 10.1007/s13369-019-04124-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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